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Re31
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2024-08-16T15:36:09
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MD_8072777543375650454349539
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2023-12-01T22:58:16
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CO_1110491338374588467010926
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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2024-08-16T15:36:09
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MD_5276451162749980934843793
null
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2023-12-01T22:58:16
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CO_1110513897081442478406855
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
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MD_1213582242930949697188121
2024-08-16T14:14:30
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2023-12-01T22:58:16
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CO_1111776808093337756091404
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T15:32:12
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MD_3140906615584827818889926
null
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2023-12-01T22:58:16
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CO_1112087300469614493617889
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:14:14
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MD_3140906615584827818889926
null
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2023-12-01T22:58:16
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CO_1112282224507310857242729
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
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MD_1213582242930949697188121
2024-08-16T14:50:04
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MD_3140906615584827818889926
null
[ "Re_iter0_T875_0_mp-8_elastic_B222_dist03_3_19" ]
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2023-12-01T22:58:16
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CO_1112622504504573497913703
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
Re
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MD_1213582242930949697188121
2024-08-16T15:26:09
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PO_1063713167495393428216946
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_8_875_4" ]
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2023-12-01T22:58:16
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CO_1116205407096850351839786
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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MD_1213582242930949697188121
2024-08-16T15:31:25
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null
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2023-12-01T22:58:16
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CO_1116640126877008270414407
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
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MD_1213582242930949697188121
2024-08-16T14:33:45
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PO_3011431815250461247418420
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_dbPP_875_19" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1116957608463512016371112
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re31
Re
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:24:20
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PO_6720489769096972818806267
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MD_5276451162749980934843793
null
[ "Re_iter0_T3500_3_mp-8642_vacancies_Vac_0_2" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1118559114082582761851532
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
[ [ 1, 1, 1 ] ]
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
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MD_1213582242930949697188121
2024-08-16T15:01:42
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PO_1899101774870769200722784
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MD_2333412701806194962250672
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_8_3500_7" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1119343924700607865784083
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
A
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MD_1213582242930949697188121
2024-08-16T14:13:06
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_crowdionB_3500_2" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1119527000817757892944147
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T14:33:12
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2023-12-01T22:58:16
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CO_1119699700206463867094941
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:58:56
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PO_6949880523710208342843138
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MD_1951564499902567866502008
null
[ "Re_iter2_0_mp-8_elastic_B222_dist03_10_875_0" ]
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2023-12-01T22:58:16
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CO_1120332918247601114668057
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:23:01
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PO_1101681712670684690927281
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MD_8072777543375650454349539
null
[ "Re_iter0_T3500_1_mp-1186901_vacancies_Vac_0_6" ]
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2023-12-01T22:58:16
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CO_1120333493892565233508464
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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2024-08-16T15:29:50
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MD_3894327761601644436733559
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[ "Re_iter2_0_mp-8_elastic_B222_dist03_2_3500_8" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1121246779470391384841702
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:06:37
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MD_8072777543375650454349539
null
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[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1121776894661056231176987
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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MD_1213582242930949697188121
2024-08-16T14:13:01
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MD_8072777543375650454349539
null
[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_3_30" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1124561375256379308080147
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:00:55
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PO_4691034738191314270306387
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MD_2333412701806194962250672
null
[ "Re_iter2_3_mp-8642_elastic_B222_dist03_1_3500_3" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1125569978753251620062030
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T14:12:39
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PO_1210707322300773051610303
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MD_1951564499902567866502008
null
[ "Re_iter2_0_mp-8_elastic_B222_dist03_5_875_2" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1126922843051148927728836
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
A
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MD_1213582242930949697188121
2024-08-16T15:22:33
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MD_2333412701806194962250672
null
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2023-12-01T22:58:16
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CO_1128036388194955319513600
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
Re
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MD_1213582242930949697188121
2024-08-16T14:13:53
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MD_3580205984756795750502668
null
[ "Re_iter2_sc_elastic_B222_dist03_1_3500_2" ]
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2023-12-01T22:58:16
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CO_1129772291084110379418387
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T15:10:50
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PO_5671573224196604668705268
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MD_3140906615584827818889926
null
[ "Re_iter0_T875_0_mp-8_elastic_B222_dist03_10_1" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1129891788818319329835524
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
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MD_1213582242930949697188121
2024-08-16T14:12:57
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23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T14:13:03
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MD_3140906615584827818889926
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2023-12-01T22:58:16
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CO_1135003225589766565663747
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T15:30:56
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MD_3140906615584827818889926
null
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2023-12-01T22:58:16
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CO_1135133375179504754950648
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T14:33:36
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MD_1951564499902567866502008
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23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
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MD_1213582242930949697188121
2024-08-16T14:34:48
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MD_3140906615584827818889926
null
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2023-12-01T22:58:16
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CO_1136180947612734603580645
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
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MD_1213582242930949697188121
2024-08-16T15:28:01
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PO_1062254712581582196388460
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MD_3894327761601644436733559
null
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2023-12-01T22:58:16
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CO_1136804853489067500747003
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:17:23
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MD_8072777543375650454349539
null
[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_8_2", "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_8_16" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1137167655611145190851134
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
Re
A
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VASP
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MD_1213582242930949697188121
2024-08-16T15:31:31
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_9_875_2" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1137448259816119202492540
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T14:34:36
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PO_2260914522448715399622672
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MD_3894327761601644436733559
null
[ "Re_iter2_0_mp-8_elastic_B222_dist03_6_3500_1" ]
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2023-12-01T22:58:16
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CO_1137631886603448055340541
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
A
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CO_1137905300427243536787574
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:13:23
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_10_3500_15" ]
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2023-12-01T22:58:16
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CO_1141751534990860246906398
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:37:37
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MD_8072777543375650454349539
null
[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_3_29", "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_3_34" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1141914723525610468272768
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T14:36:16
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2023-12-01T22:58:16
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CO_1142355351898255998792488
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:31:08
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MD_3140906615584827818889926
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2023-12-01T22:58:16
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CO_1143737545658153197476121
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:12:50
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PO_6770721881000593200912596
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MD_2333412701806194962250672
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_8_3500_12" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1144638393551371727859891
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
A
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VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T15:35:24
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_crowdionP_875_11" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1144649663382414266414119
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
Re
A
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MD_1213582242930949697188121
2024-08-16T14:12:47
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_7_875_15" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1146374609626600134479964
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re7
Re
A
[ 75, 75, 75, 75, 75, 75, 75 ]
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MD_1213582242930949697188121
2024-08-16T14:59:04
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MD_3580205984756795750502668
null
[ "Re_iter1_sc_vacancies_Vac_0_3500_13" ]
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2023-12-01T22:58:16
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CO_1146649322787662200220890
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Re" ]
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2023-12-01T17:58:30
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
Re
A
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:17:37
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MD_8097482567437995173613322
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[ "Re_iter1_sc_elastic_B222_dist03_6_875_10" ]
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2023-12-01T22:58:16
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CO_1148516802957709376900991
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T14:49:46
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MD_1951564499902567866502008
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2023-12-01T22:58:16
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CO_1149248063857847290051237
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T15:24:40
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_0_875_0" ]
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2023-12-01T22:58:16
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CO_1149874249462364570112475
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
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MD_1213582242930949697188121
2024-08-16T14:12:17
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_interOhB_3500_8" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1150840003805237201608748
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:24:45
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MD_3140906615584827818889926
null
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[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1153852699980806670795966
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:11:01
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null
[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_0_2" ]
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2023-12-01T22:58:16
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CO_1156134388363219546520413
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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MD_1213582242930949697188121
2024-08-16T14:51:52
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MD_5276451162749980934843793
null
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23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:14:11
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MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_interstitials_HCP2_dbB_13" ]
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2023-12-01T22:58:16
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CO_1158180958682532173405796
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T14:34:07
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PO_1175845857047281173755199
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MD_3140906615584827818889926
null
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2023-12-01T22:58:16
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CO_1159532593708876493231502
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:11:49
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2023-12-01T22:58:16
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CO_1164311887090273978720795
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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CO_1164586642595257019175774
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:13:35
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2023-12-01T22:58:16
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CO_1165133285236859848280122
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:59:55
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PO_5794110590093836373460309
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MD_8072777543375650454349539
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[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_0_0" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1167642641238221419020503
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:49:47
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MD_3894327761601644436733559
null
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[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1169911950417679946519856
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:12:06
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MD_5276451162749980934843793
null
[ "Re_iter0_T875_3_mp-8642_elastic_B222_dist03_2_11" ]
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2023-12-01T22:58:16
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CO_1170995166072187347496511
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
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MD_1213582242930949697188121
2024-08-16T14:17:28
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_1_3500_6" ]
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2023-12-01T22:58:16
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CO_1171133861671581475695772
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:37:45
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MD_3894327761601644436733559
null
[ "Re_iter2_0_mp-8_interstitials_HCP2_dbB_3500_5" ]
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2023-12-01T22:58:16
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CO_1173050678796859029763843
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
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MD_1213582242930949697188121
2024-08-16T14:14:26
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PO_7165159214973174540847769
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_interOh_875_0" ]
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2023-12-01T22:58:16
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CO_1174317959605366338809250
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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MD_1213582242930949697188121
2024-08-16T14:36:43
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MD_5276451162749980934843793
null
[ "Re_iter0_T3500_3_mp-8642_elastic_B222_dist03_4_6" ]
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2023-12-01T22:58:16
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CO_1174602209099112886559182
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:13:08
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_interTdB_3500_8" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1175311816662049550927020
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
A
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MD_1213582242930949697188121
2024-08-16T14:12:06
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PO_1105423495223255677385683
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MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_interstitials_HCP2_interTdB_16" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1176214876237928656272378
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
A
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MD_1213582242930949697188121
2024-08-16T15:15:54
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MD_8072777543375650454349539
null
[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_8_9" ]
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2023-12-01T22:58:16
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CO_1178031294001682255818402
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:36:12
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PO_8333684686493557470878661
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MD_2333412701806194962250672
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_9_3500_8" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1178639712522271852008249
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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MD_4820518588507787498309475
null
[ "Re_iter2_3_mp-8642_elastic_B222_dist03_6_875_8" ]
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2023-12-01T22:58:16
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CO_1179959377981705159307625
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:40:16
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MD_5276451162749980934843793
null
[ "Re_iter0_T875_3_mp-8642_elastic_B222_dist03_1_12" ]
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2023-12-01T22:58:16
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CO_1182008212695211592043242
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
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MD_1213582242930949697188121
2024-08-16T15:04:14
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PO_1844131338586123680688521
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MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_interstitials_HCP2_crowdion_15" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1182054303182351805825834
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:14:36
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PO_1448199615512873079188321
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MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_elastic_B222_dist03_9_17" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1183062104925321997225238
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
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MD_1213582242930949697188121
2024-08-16T15:04:07
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PO_1010684113406185207290144
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MD_4820518588507787498309475
null
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[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1184235953653905479773651
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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CO_1186165086800083424467222
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:07:01
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_3_875_14" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1189543416296029663952160
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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MD_1213582242930949697188121
2024-08-16T14:14:16
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PO_1134669646978441225503337
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MD_4820518588507787498309475
null
[ "Re_iter2_3_mp-8642_elastic_B222_dist03_8_875_7" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1189884585054666102360282
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
A
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2024-08-16T15:17:26
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CO_1191708301063964303180257
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:29:16
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1192357438853985874800284
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
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MD_1213582242930949697188121
2024-08-16T14:51:43
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PO_6458275355803986737728899
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_interOh_875_18" ]
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2023-12-01T22:58:16
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CO_1192665728395445393990644
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
Re
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MD_1213582242930949697188121
2024-08-16T15:12:30
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_4_875_14" ]
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2023-12-01T22:58:16
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CO_1192770842537555463553508
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
Re
A
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VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T15:24:29
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MD_3580205984756795750502668
null
[ "Re_iter2_sc_elastic_B222_dist03_4_3500_6" ]
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2023-12-01T22:58:16
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CO_1193074500024064704567135
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
A
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MD_1213582242930949697188121
2024-08-16T14:13:21
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MD_3894327761601644436733559
null
[ "Re_iter2_0_mp-8_interstitials_HCP2_db_3500_1" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1193588639913884851305958
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T15:29:28
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MD_3140906615584827818889926
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2023-12-01T22:58:16
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CO_1195529021594842391752064
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
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MD_1213582242930949697188121
2024-08-16T14:53:59
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MD_1951564499902567866502008
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2023-12-01T22:58:16
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CO_1197265990839250112842456
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
A
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MD_1213582242930949697188121
2024-08-16T15:12:50
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PO_1126857489839196097293325
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MD_3140906615584827818889926
null
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2023-12-01T22:58:16
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CO_1197304825347018252640777
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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MD_1213582242930949697188121
2024-08-16T15:04:18
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MD_5276451162749980934843793
null
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2023-12-01T22:58:16
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CO_1197977861551040353494871
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:00:49
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2023-12-01T22:58:16
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CO_1198508848002121475278012
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
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MD_1213582242930949697188121
2024-08-16T14:13:18
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PO_1933303705068051310389178
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_5_875_0" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1199060217497363135830000
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re31
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MD_1213582242930949697188121
2024-08-16T14:13:49
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PO_4179329519027143966744129
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MD_5276451162749980934843793
null
[ "Re_iter0_T875_3_mp-8642_vacancies_Vac_0_18" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1199585368347471742804558
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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MD_1213582242930949697188121
2024-08-16T15:22:22
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PO_3473249060189795143779374
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MD_4820518588507787498309475
null
[ "Re_iter2_3_mp-8642_elastic_B222_dist03_1_875_3" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1199704140639835375967130
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Re" ]
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2023-12-01T17:58:30
[ [ 1, 1, 1 ] ]
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[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
A
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2024-08-16T14:59:02
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2023-12-01T22:58:16
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23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:12:39
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MD_1951564499902567866502008
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2023-12-01T22:58:16
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CO_1199972868545831904990512
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
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23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
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MD_1213582242930949697188121
2024-08-16T15:00:01
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PO_1423202364753188255784232
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MD_3894327761601644436733559
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[ "Re_iter2_0_mp-8_interstitials_HCP2_dbPP_3500_3" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1200738076406643971813162
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
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MD_1213582242930949697188121
2024-08-16T14:15:47
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{"materials-project-id": "mp-8642", "temperature": 3500, "hash": "2333412701806194962250672412351887755010813328886382891008025698246224040567077662483682371323617452689980898265035030575180496515195647187485047238158109", "id": "MD_2333412701806194962250672"}
MD_2333412701806194962250672
null
[ "Re_iter2_3_mp-8642_elastic_B222_dist03_3_3500_5" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1201533765964101982705948
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Re" ]
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2023-12-01T17:58:30
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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2024-08-16T14:13:10
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2023-12-01T22:58:16
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CO_1204085089502465522386454
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:26:28
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PO_1106024706045614034336880
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1204136363462858906599662
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:55:02
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MD_4820518588507787498309475
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_9_875_1" ]
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2023-12-01T22:58:16
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CO_1205320008512075813051570
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
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MD_1213582242930949697188121
2024-08-16T14:30:40
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MD_3140906615584827818889926
null
[ "Re_iter0_T875_0_mp-8_interstitials_HCP2_dbPP_14" ]
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2023-12-01T22:58:16
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CO_1206108570189030008162073
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Re" ]
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
Re
A
[ 75, 75, 75, 75, 75, 75, 75, 75 ]
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VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T15:00:22
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PO_2467804563169081617785312
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_5_875_13" ]
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2023-12-01T22:58:16
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CO_1209869166988503879862700
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
A
[ 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75 ]
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1
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MD_1213582242930949697188121
2024-08-16T14:30:59
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PO_4523851794643421438337151
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_interOh_3500_12" ]
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2023-12-01T22:58:16
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CO_1210451636455928244534294
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
A
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1
VASP
DFT-PBE
null
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null
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true
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2.447397
4.841944
{"input": {"ALGO": "fast", "EDIFF": "1E-8", "ENCUT": "400", "IBRION": "0", "ICHARG": "0", "ISIF": "2", "ISMEAR": "1", "ISTART": "0", "ISYM": "0", "KBLOCK": "10", "KGAMMA": "F", "KPAR": "16", "KSPACING": "0.24", "LCHARG": "T", "LREAL": "F", "LWAVE": "F", "MAXMIX": "50", "NBLOCK": "1", "NELM": "200", "NELMIN": "4", "NPAR": "8", "POTIM": "2", "PREC": "A", "PSTRESS": "0", "SIGMA": "0.15", "SMASS": "-1", "file-type": "INCAR"}, "hash": "12135822429309496971881212100548754870478961791137930949625877367285087883313386750731592539663054471050405358418449513543996992751906584969573924479043013", "id": "MD_1213582242930949697188121"}
MD_1213582242930949697188121
2024-08-16T15:26:59
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PO_2669235419084863918018934
{"materials-project-id": "mp-8642", "temperature": 875, "hash": "4820518588507787498309475974572485981888251467462188826379741861055800348663208623625121292514595542784805618367869818107146036450004379793983452396383543", "id": "MD_4820518588507787498309475"}
MD_4820518588507787498309475
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_3_875_11" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1210905973806558044475780
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Re" ]
1
5,027
5,029
101,248
0
5,027
0
5,027
0
5,027
-208.974685
8,714.473585
0
2023-12-01T17:58:30
[ [ 1, 1, 1 ] ]
[ 3 ]
2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
2989724594271379140693076950335437316813632529496723537825365549542244322666453955313072211183829553508450816956989177903944526163819938242770028661290197
DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0